Biologists need to perform complex queries, often across a variety of databases. Typically, each data resource provides an advanced query interface, each of which must be learnt by the biologist before they can begin to query them. Frequently, more than one data source is required and for high-throughput analysis, cutting and pasting results between websites is certainly very time consuming. Therefore, many groups rely on local bioinformatics support to process queries by accessing the resource's programmatic interfaces if they exist. This is not an efficient solution in terms of cost and time. Instead, it would be better if the biologist only had to learn one generic interface. BioMart provides such a solution.

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BioMart – biological queries made easy

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer, and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings, and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. The software creates and manages a type of organism-specific database called a Pathway/Genome Database (PGDB), which the software enables database curators to interactively edit. It supports web publishing of PGDBs and provides a large number of query, visualization, and omics-data analysis tools. Scientists around the world have created more than 9,800 PGDBs by using Pathway Tools, many of which are curated databases for important model organisms. Those PGDBs can be exchanged using a peer-to-peer database-sharing system called the PGDB Registry.

Pathway Tools version 23.0: Integrated Software for Pathway/Genome Informatics and Systems Biology

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms.

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

Transcription factors (TFs) are key regulatory proteins that enhance or repress the transcriptional rate of their target genes by binding to specific promoter regions (i.e. cis-acting elements) upon activation or de-activation of upstream signaling cascades. TFs thus constitute master control elements of dynamic transcriptional networks. TFs have fundamental roles in almost all biological processes (development, growth and response to environmental factors) and it is assumed that they play immensely important functions in the evolution of species. In plants, TFs have been employed to manipulate various types of metabolic, developmental and stress response pathways. Cross-species comparison and identification of regulatory modules and hence TFs is thought to become increasingly important for the rational design of new plant biomass. Up to now, however, no computational repository is available that provides access to the largely complete sets of transcription factors of sequenced plant genomes. PlnTFDB is an integrative plant transcription factor database that provides a web interface to access large (close to complete) sets of transcription factors of several plant species, currently encompassing Arabidopsis thaliana (thale cress), Populus trichocarpa (poplar), Oryza sativa (rice), Chlamydomonas reinhardtii and Ostreococcus tauri. It also provides an access point to its daughter databases of a species-centered representation of transcription factors (OstreoTFDB, ChlamyTFDB, ArabTFDB, PoplarTFDB and RiceTFDB). Information including protein sequences, coding regions, genomic sequences, expressed sequence tags (ESTs), domain architecture and scientific literature is provided for each family. We have created lists of putatively complete sets of transcription factors and other transcriptional regulators for five plant genomes. They are publicly available through http://plntfdb.bio.uni-potsdam.de
 . Further data will be included in the future when the sequences of other plant genomes become available.

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PlnTFDB: an integrative plant transcription factor database

The grass family comprises the most important cereal crops and is a good system for studying, with comparative genomics, mechanisms of evolution, speciation, and domestication. Here, we identified and characterized the evolution of shared duplications in the rice (Oryza sativa) and wheat (Triticum aestivum) genomes by comparing 42,654 rice gene sequences with 6426 mapped wheat ESTs using improved sequence alignment criteria and statistical analysis. Intraspecific comparisons identified 29 interchromosomal duplications covering 72% of the rice genome and 10 duplication blocks covering 67.5% of the wheat genome. Using the same methodology, we assessed orthologous relationships between the two genomes and detected 13 blocks of colinearity that represent 83.1 and 90.4% of the rice and wheat genomes, respectively. Integration of the intraspecific duplications data with colinearity relationships revealed seven duplicated segments conserved at orthologous positions. A detailed analysis of the length, composition, and divergence time of these duplications and comparisons with sorghum (Sorghum bicolor) and maize (Zea mays) indicated common and lineage-specific patterns of conservation between the different genomes. This allowed us to propose a model in which the grass genomes have evolved from a common ancestor with a basic number of five chromosomes through a series of whole genome and segmental duplications, chromosome fusions, and translocations.

Identification and Characterization of Shared Duplications between Rice and Wheat Provide New Insight into Grass Genome Evolution

Rice, maize, sorghum, wheat, barley and the other major crop grasses from the family Poaceae (Gramineae) are mankind’s most important source of calories and contribute tens of billions of dollars annually to the world economy (FAO 1999, http:// www.fao.org; USDA 1997, http://www.usda.gov). Continued improvement of Poaceae crops is necessary in order to continue to feed an ever-growing worldpopulation.However,ofthemajorcropgrasses, only rice (Oryza sativa), with a compact genome of � 400 Mbp, has been sequenced and annotated. The Gramene database (http://www.gramene.org) takes advantage of the known genetic colinearity (synteny) between rice and the major crop plant genomes to provide maize, sorghum, millet, wheat, oat and barley researchers with the benefits of an annotated genome years before their own species are sequenced. Gramene is a one stop portal for finding curated literature, genetic and genomic datasets related to maps, markers, genes, genomes and quantitative trait loci. The addition of several new tools to Gramene has greatly facilitated the potential for comparative analysis among the grasses and contributes to our understanding of the anatomy, development, environmental responses and the factors influencing agronomic performance of cereal crops. Since the last publication on Gramene database by D. H. Ware, P. Jaiswal, J. Ni, I. V. Yap, X. Pan, K. Y. Clark, L. Teytelman, S. C. Schmidt, W. Zhao, K.Changetal.[(2002),PlantPhysiol.,130,1606–1613], the database has undergone extensive changes that are described in this publication.

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Benjamin P Faga

Papers

Gramene: a bird's eye view of cereal genomes